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6 Famous Folk Who Once Drove Taxis

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In some cities, driving a taxi is considered an important, valued, even elevated vocation. In London, for example, you need to study and train for about three years before you can get a license. Three fourths of those who begin the taxi training course, never make it to the end. Because of the seriousness with which they take the job, London cab drivers have even been the subjects of brain studies, which have discovered that the cabbies have a larger hippocampus compared with other people.

Unfortunately, here, on the other side of the pond, cabbies are usually looked down upon. But maybe this list of famous folk who spent time driving taxis will help change the image a little.

1. Larry David

larrydavid-thumb-257x278Who can't picture the misanthropic funny-man behind Seinfeld and Curb Your Enthusiasm driving a taxi? In truth, David's early career was peppered with a whole host of odd jobs, including limousine driver and--strapped into your parachutes?--bra salesman! Pretty appropriate career choice for the real life George Costanza, eh?

Now Hail This: When David worked as a cabbie, he was living across the hall from Kenny Kramer, who would later serve as the inspiration for Michael Richards' character on Seinfeld.

2. David Mamet

davidmamet460The Pulitzer Prize winning playwright credits his brief period as a Chicago cab driver as on-the-job training for his later career as a writer. Mamet often decried the notion that real writers were trained in the halls of Ivy League institutions and looked to "knockaround guys" like Jack London, Nelson Algren and Ernest Hemingway as his inspiration.

Now Hail This: When it comes to writing, Mamet values life experience over technique and will often compare his favorite writers to cab drivers.

3. Danny Glover

danny-gloverIn 1999, the actor best known for playing an over-the-hill cop in the Lethal Weapon movies, used his leverage as a former San Francisco cab driver to raise awareness about African Americans being passed over for white passengers. In response, Rudolph Giuliani launched Operation Refusal, which suspended the licenses of cab drivers who favored white passengers over black ones.

Now Hail This: Glover's much publicized outrage has spawned countless Internet parodies, aptly titled "The Danny Glove Cab Test." Watch it here.

4. Jimmy Smits

manifesto-jimmy-smits-yl-deHe may have his Masters in Dramatic Arts from Cornell, but for a brief period in the early "˜80s, Jimmy Smits played chauffeur to dozens of rowdy New Yorkers. The cabbie gig lasted only a few months, until he received the pilot script for a new show producer Steven Bochco was developing called LA Law. After failing to impress NBC Executives, Smits booked a $99 flight to the West Coast to audition for Bochco in person.

Now Hail This: As a struggling New York theater actor, Smits acted in off-Broadway plays during the day while driving a cab at night.

5. Paul Stanley

0_61_stanley_paulThe early days of Kiss were not very glamorous for Paul Stanley. His parents were convinced his obsession with rock music was just a fad, and threatened to cut off their schnorer son. What's a guitar wielding frontman of a dingy rock-n-roll band to do? Take a part time job as a cab driver, of course.

Now Hail This: One of the most frequent stops on Stanley's route was Madison Square Garden, where he would drive customers to see everything from Knicks games to Elvis concerts.

6. Philip Glass

070219_glassBefore he penned film scores for The Truman Show and Notes on a Scandal, Philip Glass was just another Julliard-trained composer struggling to make a living in New York City. It was behind the wheel of a cab that Glass worked on Einstein on the Beach, his most recognized opera. Glass loved the independence of being a cab driver, and he kept the job until he was able to earn a living from his music. Of course, financially, he is now the most successful living "˜classical' composer in the world.

Now Hail This: While still a relatively unknown composer, a female customer entered Glass's cab and recognized his music blaring form the stereo. Glass later surprised the woman by revealing his identity.

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iStock // Ekaterina Minaeva
technology
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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Animals
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Scientists Think They Know How Whales Got So Big
May 24, 2017
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iStock

It can be difficult to understand how enormous the blue whale—the largest animal to ever exist—really is. The mammal can measure up to 105 feet long, have a tongue that can weigh as much as an elephant, and have a massive, golf cart–sized heart powering a 200-ton frame. But while the blue whale might currently be the Andre the Giant of the sea, it wasn’t always so imposing.

For the majority of the 30 million years that baleen whales (the blue whale is one) have occupied the Earth, the mammals usually topped off at roughly 30 feet in length. It wasn’t until about 3 million years ago that the clade of whales experienced an evolutionary growth spurt, tripling in size. And scientists haven’t had any concrete idea why, Wired reports.

A study published in the journal Proceedings of the Royal Society B might help change that. Researchers examined fossil records and studied phylogenetic models (evolutionary relationships) among baleen whales, and found some evidence that climate change may have been the catalyst for turning the large animals into behemoths.

As the ice ages wore on and oceans were receiving nutrient-rich runoff, the whales encountered an increasing number of krill—the small, shrimp-like creatures that provided a food source—resulting from upwelling waters. The more they ate, the more they grew, and their bodies adapted over time. Their mouths grew larger and their fat stores increased, helping them to fuel longer migrations to additional food-enriched areas. Today blue whales eat up to four tons of krill every day.

If climate change set the ancestors of the blue whale on the path to its enormous size today, the study invites the question of what it might do to them in the future. Changes in ocean currents or temperature could alter the amount of available nutrients to whales, cutting off their food supply. With demand for whale oil in the 1900s having already dented their numbers, scientists are hoping that further shifts in their oceanic ecosystem won’t relegate them to history.

[h/t Wired]

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